1 Goal of the script

This script plots the sensors data from the Smarttester.

dir_in <- "analysis/derived_data/"
dir_plots <- "analysis/plots/"

Input CSV file file must be located in “./analysis/derived_data/”.
Plots will be saved in “./analysis/plots/”.

The knit directory for this script is the project directory.

2 Load packages

library(ggplot2)
library(grateful)
library(gridExtra)
library(knitr)
library(R.utils)
library(rmarkdown)
library(tidyverse)
library(viridis)

3 Read in Rbin file

ST_file <- list.files(dir_in, pattern = "Smarttester\\.Rbin$", full.names = TRUE)
ST_data <- loadObject(ST_file)
str(ST_data)
'data.frame':   114195 obs. of  10 variables:
 $ Sample           : chr  "ISEA-EX1" "ISEA-EX1" "ISEA-EX1" "ISEA-EX1" ...
 $ File             : num  0 0 0 0 0 0 0 0 0 0 ...
 $ Bamboo_position  : Factor w/ 5 levels "0","-7.5","-15",..: 1 1 1 1 1 1 1 1 1 1 ...
 $ Step             : int  0 100000 200000 300000 400000 500000 600000 700000 800000 900000 ...
 $ StrokeNr         : num  1 1 1 1 1 1 2 2 2 2 ...
 $ Angle [°]        : num  0.000884 -0.016282 -0.589631 -0.811417 -0.699494 ...
 $ Depth [mm]       : num  10.15 10.15 9.92 9.36 9.23 ...
 $ Torque [Nm]      : num  1.4 1.6 4.9 5.7 6.3 7 8.2 -3.9 -2.7 -4.2 ...
 $ X_position [mm]  : num  275 275 279 284 285 ...
 $ X_velocity [mm/s]: num  0.00187 9.88465 59.21647 31.58108 0.39584 ...
head(ST_data)
    Sample File Bamboo_position   Step StrokeNr     Angle [°] Depth [mm]
1 ISEA-EX1    0               0      0        1  0.0008842885  10.151439
2 ISEA-EX1    0               0 100000        1 -0.0162818470  10.146061
3 ISEA-EX1    0               0 200000        1 -0.5896308000   9.922504
4 ISEA-EX1    0               0 300000        1 -0.8114173000   9.362462
5 ISEA-EX1    0               0 400000        1 -0.6994940600   9.229558
6 ISEA-EX1    0               0 500000        1 -0.6383826000   9.255678
  Torque [Nm] X_position [mm] X_velocity [mm/s]
1         1.4        275.0000       0.001873783
2         1.6        275.1974       9.884645000
3         4.9        279.2093      59.216473000
4         5.7        284.2325      31.581081000
5         6.3        284.9546       0.395838140
6         7.0        284.9808       0.040469542

4 Plot

4.1 Define variables

Define dependent (numeric) variables to plot on the Y axis

# Y-axis
ST_y <- c("X_velocity [mm/s]", "Depth [mm]", "Angle [°]", "Torque [Nm]")

# X-axis
X_name <- grep("X_position", names(ST_data), value = TRUE)
X_name_leg <- gsub("_", " ", X_name)

4.2 Subset and prepare data for plots

For readability, only every 20th stroke will be plotted. The first 50 strokes going along the positive X axis (i.e. odd strokes from 1 to 100) will also be plotted separately.

4.2.1 Every 20th strokes

# Create a sequence of every 20th strokes, including first and before last strokes
# Before last is necessary because of bidirectional strokes:
# the odd strokes go in one X direction, while the even strokes go in the other
stroke_20 <- seq(1, 2000, by = 20) %>% 
             c(max(ST_data$StrokeNr) - 1) 

# Extract data for these strokes
data_every20 <- filter(ST_data, StrokeNr %in% stroke_20) %>% 

                # Pivot to longer format for facet plots
                pivot_longer(all_of(ST_y), names_to = "parameter", values_to = "value") %>% 
  
                # Convert to data.frame
                as.data.frame()

# Check result
str(data_every20)
'data.frame':   24232 obs. of  8 variables:
 $ Sample         : chr  "ISEA-EX1" "ISEA-EX1" "ISEA-EX1" "ISEA-EX1" ...
 $ File           : num  0 0 0 0 0 0 0 0 0 0 ...
 $ Bamboo_position: Factor w/ 5 levels "0","-7.5","-15",..: 1 1 1 1 1 1 1 1 1 1 ...
 $ Step           : int  0 0 0 0 100000 100000 100000 100000 200000 200000 ...
 $ StrokeNr       : num  1 1 1 1 1 1 1 1 1 1 ...
 $ X_position [mm]: num  275 275 275 275 275 ...
 $ parameter      : chr  "X_velocity [mm/s]" "Depth [mm]" "Angle [°]" "Torque [Nm]" ...
 $ value          : num  1.87e-03 1.02e+01 8.84e-04 1.40 9.88 ...
head(data_every20)
    Sample File Bamboo_position   Step StrokeNr X_position [mm]
1 ISEA-EX1    0               0      0        1        275.0000
2 ISEA-EX1    0               0      0        1        275.0000
3 ISEA-EX1    0               0      0        1        275.0000
4 ISEA-EX1    0               0      0        1        275.0000
5 ISEA-EX1    0               0 100000        1        275.1974
6 ISEA-EX1    0               0 100000        1        275.1974
          parameter        value
1 X_velocity [mm/s] 1.873783e-03
2        Depth [mm] 1.015144e+01
3         Angle [°] 8.842885e-04
4       Torque [Nm] 1.400000e+00
5 X_velocity [mm/s] 9.884645e+00
6        Depth [mm] 1.014606e+01

4.2.2 First 50 positive (odd) strokes

# Extract data for the first 50 odd strokes
data_1to50 <- filter(ST_data, StrokeNr %in% seq(1, 100, 2)) %>% 

              # Pivot to longer format for facet plots
              pivot_longer(all_of(ST_y), names_to = "parameter", values_to = "value") %>% 
  
              # Convert to data.frame
              as.data.frame()

# Check result
str(data_1to50)
'data.frame':   10500 obs. of  8 variables:
 $ Sample         : chr  "ISEA-EX1" "ISEA-EX1" "ISEA-EX1" "ISEA-EX1" ...
 $ File           : num  0 0 0 0 0 0 0 0 0 0 ...
 $ Bamboo_position: Factor w/ 5 levels "0","-7.5","-15",..: 1 1 1 1 1 1 1 1 1 1 ...
 $ Step           : int  0 0 0 0 100000 100000 100000 100000 200000 200000 ...
 $ StrokeNr       : num  1 1 1 1 1 1 1 1 1 1 ...
 $ X_position [mm]: num  275 275 275 275 275 ...
 $ parameter      : chr  "X_velocity [mm/s]" "Depth [mm]" "Angle [°]" "Torque [Nm]" ...
 $ value          : num  1.87e-03 1.02e+01 8.84e-04 1.40 9.88 ...
head(data_1to50)
    Sample File Bamboo_position   Step StrokeNr X_position [mm]
1 ISEA-EX1    0               0      0        1        275.0000
2 ISEA-EX1    0               0      0        1        275.0000
3 ISEA-EX1    0               0      0        1        275.0000
4 ISEA-EX1    0               0      0        1        275.0000
5 ISEA-EX1    0               0 100000        1        275.1974
6 ISEA-EX1    0               0 100000        1        275.1974
          parameter        value
1 X_velocity [mm/s] 1.873783e-03
2        Depth [mm] 1.015144e+01
3         Angle [°] 8.842885e-04
4       Torque [Nm] 1.400000e+00
5 X_velocity [mm/s] 9.884645e+00
6        Depth [mm] 1.014606e+01

4.3 Prepare receiving lists

Data for the first 400 strokes of sample ISEA-EX3 were not recorded, so the first 50 positive strokes cannot be plotted for that sample.

# Sample IDs
sample_ID <- levels(factor(ST_data$Sample)) %>% 
             data.frame(Sample = ., SampleNr = .) %>% 
             mutate(SampleNr = as.numeric(gsub("ISEA-EX", "", SampleNr))) %>% 
             arrange(SampleNr)

# Create lists to receive the plots
p_every20 <- p_1to50 <- vector(mode = "list", length = nrow(sample_ID))
names(p_every20) <- names(p_1to50) <- sample_ID$Sample

# Delete ISEA-EX3 from p_1to50
p_1to50[["ISEA-EX3"]] <- NULL

4.4 Plots

4.4.1 Every 20th stroke

# Plot for every sample
for (i in names(p_every20)) {
  
  # Filter data per sample
  data_every20_i <- filter(data_every20, Sample == i)
  
                    # Prepare plot
  p_every20[[i]] <- ggplot(data = data_every20_i, 
                           aes(x = .data[[X_name]], y = value, color = StrokeNr)) + 
  
                    # Draw one line per stroke
                    geom_line(aes(group = StrokeNr), alpha = 0.7, linewidth = 0.4) +
  
                    # Facet plot by 'parameter' (= 'ST_y')
                    facet_wrap(~ parameter, scales = "free_y") +
  
                    # The palette 'viridis' is printer- and colorblind-friendly, and perceptually uniform
                    scale_color_viridis(trans = "reverse") + 
  
                    # Light theme, and remove x-axis text and ticks
                    theme_classic() + 
                    
                    # No y-axis label and title from sample_ID$Sample
                    labs(y = NULL, title = i, x = X_name_leg)
}

# Print list of plots
print(p_every20)
$`ISEA-EX1`


$`ISEA-EX2`


$`ISEA-EX3`


$`ISEA-EX4`


$`ISEA-EX5`


$`ISEA-EX6`


$`ISEA-EX7`


$`ISEA-EX8`


$`ISEA-EX9`


$`ISEA-EX10`


$`ISEA-EX11`


$`ISEA-EX12`

# Save list of plots
ggsave(filename = "ISEA_use-wear_Smarttester-plots_all-strokes.pdf", 
       path = dir_plots, width = 190, units = "mm", 
       plot = marrangeGrob(p_every20, nrow = 1, ncol = 1, top = NULL))

4.4.2 First 50 strokes

Data for the first 400 strokes of sample ISEA-EX3 were not recorded, so the first 50 positive strokes cannot be plotted for that sample.

# Plot for every sample
for (i in names(p_1to50)) {
  
  # Filter data per sample
  data_1to50_i <- filter(data_1to50, Sample == i)
  
                  # Prepare plot
  p_1to50[[i]] <- ggplot(data = data_1to50_i, 
                         aes(x = .data[[X_name]], y = value, color = StrokeNr)) + 
  
                  # Draw one line per stroke
                  geom_line(aes(group = StrokeNr), alpha = 0.7, linewidth = 0.4) +
  
                  # Facet plot by 'parameter' (= 'ST_y')
                  facet_wrap(~ parameter, scales = "free_y") +
  
                  # The palette 'viridis' is printer- and colorblind-friendly, and perceptually uniform
                  scale_color_viridis(trans = "reverse") + 
  
                  # Light theme, and remove x-axis text and ticks
                  theme_classic() + 
                    
                  # No y-axis label and title from sample_ID$Sample
                  labs(y = NULL, title = i, x = X_name_leg)
}

# Print list of plots
print(p_1to50)
$`ISEA-EX1`


$`ISEA-EX2`


$`ISEA-EX4`


$`ISEA-EX5`


$`ISEA-EX6`


$`ISEA-EX7`


$`ISEA-EX8`


$`ISEA-EX9`


$`ISEA-EX10`


$`ISEA-EX11`


$`ISEA-EX12`

# Save list of plots
ggsave(filename = "ISEA_use-wear_Smarttester-plots_50strokes.pdf", 
       path = dir_plots, width = 190, units = "mm", 
       plot = marrangeGrob(p_1to50, nrow = 1, ncol = 1, top = NULL))

5 sessionInfo()

sessionInfo()
R version 4.4.0 (2024-04-24 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 10 x64 (build 19045)

Matrix products: default


locale:
[1] LC_COLLATE=English_United States.utf8 
[2] LC_CTYPE=English_United States.utf8   
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.utf8    

time zone: Europe/Berlin
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] viridis_0.6.5     viridisLite_0.4.2 lubridate_1.9.3   forcats_1.0.0    
 [5] stringr_1.5.1     dplyr_1.1.4       purrr_1.0.2       readr_2.1.5      
 [9] tidyr_1.3.1       tibble_3.2.1      tidyverse_2.0.0   rmarkdown_2.27   
[13] R.utils_2.12.3    R.oo_1.26.0       R.methodsS3_1.8.2 knitr_1.47       
[17] gridExtra_2.3     grateful_0.2.7    ggplot2_3.5.1    

loaded via a namespace (and not attached):
 [1] sass_0.4.9        utf8_1.2.4        generics_0.1.3    stringi_1.8.4    
 [5] hms_1.1.3         digest_0.6.35     magrittr_2.0.3    evaluate_0.23    
 [9] grid_4.4.0        timechange_0.3.0  fastmap_1.2.0     rprojroot_2.0.4  
[13] jsonlite_1.8.8    fansi_1.0.6       scales_1.3.0      textshaping_0.4.0
[17] jquerylib_0.1.4   cli_3.6.2         rlang_1.1.4       munsell_0.5.1    
[21] withr_3.0.0       cachem_1.1.0      yaml_2.3.8        tools_4.4.0      
[25] tzdb_0.4.0        colorspace_2.1-0  vctrs_0.6.5       R6_2.5.1         
[29] lifecycle_1.0.4   ragg_1.3.2        pkgconfig_2.0.3   pillar_1.9.0     
[33] bslib_0.7.0       gtable_0.3.5      glue_1.7.0        systemfonts_1.1.0
[37] highr_0.11        xfun_0.44         tidyselect_1.2.1  rstudioapi_0.16.0
[41] farver_2.1.2      htmltools_0.5.8.1 labeling_0.4.3    compiler_4.4.0

6 Cite R packages used

Package Version Citation
base 4.4.0 R Core Team (2024)
grateful 0.2.7 Rodriguez-Sanchez and Jackson (2023)
gridExtra 2.3 Auguie (2017)
knitr 1.47 Xie (2014); Xie (2015); Xie (2024)
R.methodsS3 1.8.2 Bengtsson (2003a)
R.oo 1.26.0 Bengtsson (2003b)
R.utils 2.12.3 Bengtsson (2023)
rmarkdown 2.27 Xie, Allaire, and Grolemund (2018); Xie, Dervieux, and Riederer (2020); Allaire et al. (2024)
tidyverse 2.0.0 Wickham et al. (2019)
viridis 0.6.5 Garnier et al. (2024)
viridisLite 0.4.2 Garnier et al. (2023)
RStudio 2024.4.1.748 Posit team (2024)

References

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Auguie, Baptiste. 2017. gridExtra: Miscellaneous Functions for “Grid” Graphics. https://CRAN.R-project.org/package=gridExtra.
Bengtsson, Henrik. 2003a. “The R.oo Package - Object-Oriented Programming with References Using Standard R Code.” In Proceedings of the 3rd International Workshop on Distributed Statistical Computing (DSC 2003), edited by Kurt Hornik, Friedrich Leisch, and Achim Zeileis. Vienna, Austria: https://www.r-project.org/conferences/DSC-2003/Proceedings/. https://www.r-project.org/conferences/DSC-2003/Proceedings/Bengtsson.pdf.
———. 2003b. “The R.oo Package - Object-Oriented Programming with References Using Standard R Code.” In Proceedings of the 3rd International Workshop on Distributed Statistical Computing (DSC 2003), edited by Kurt Hornik, Friedrich Leisch, and Achim Zeileis. Vienna, Austria: https://www.r-project.org/conferences/DSC-2003/Proceedings/. https://www.r-project.org/conferences/DSC-2003/Proceedings/Bengtsson.pdf.
———. 2023. R.utils: Various Programming Utilities. https://CRAN.R-project.org/package=R.utils.
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———, et al. 2024. viridis(Lite) - Colorblind-Friendly Color Maps for r. https://doi.org/10.5281/zenodo.4679423.
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Wickham, Hadley, Mara Averick, Jennifer Bryan, Winston Chang, Lucy D’Agostino McGowan, Romain François, Garrett Grolemund, et al. 2019. “Welcome to the tidyverse.” Journal of Open Source Software 4 (43): 1686. https://doi.org/10.21105/joss.01686.
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———. 2015. Dynamic Documents with R and Knitr. 2nd ed. Boca Raton, Florida: Chapman; Hall/CRC. https://yihui.org/knitr/.
———. 2024. knitr: A General-Purpose Package for Dynamic Report Generation in r. https://yihui.org/knitr/.
Xie, Yihui, J. J. Allaire, and Garrett Grolemund. 2018. R Markdown: The Definitive Guide. Boca Raton, Florida: Chapman; Hall/CRC. https://bookdown.org/yihui/rmarkdown.
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